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iclr2024_conference.tex

@@ -195,25 +195,25 @@
     	\small
     	\SetAlgoLined
     	\caption{Adiabatic Replay}\label{alg:two}
-    	\KwData{AR scholar $\Phi$, AR solver $\Theta$, real data $\mathcal{X}_{t}$, $Y_t$}
+    	\KwData{AR scholar/gen. $\Phi$, AR solver $\Theta$, real data $\mathcal{X}^{t}$, $Y^t$}
     	\For{$t \in 2...T$}{ % from T2...TN
     		\For{$\mathcal{B}_{N} \sim \mathcal{X}_{t}$}{ % iterate over merged batches
-    			\tcp{Query scholar $\Phi$.}
-    			$\sigma_{\mathcal{B}_{N}} \gets Forward(\Phi, \mathcal{B}_{N})$\;
+    			\tcp{Propagate batch $\mathcal B_N$ though $\Phi$.}
+    			$\sigma_{\mathcal{B}_{N}} \gets \Phi(\mathcal{B}_{N})$\;
     			% forward call on DCGMM with batch xs, returns logits from top layer
-      			\tcp{Sample from the GMM of $\Phi$.}    			
-    			$\mathcal{B}_{G} \gets SampleOp(\Phi, \sigma_{\mathcal{B}_{N}})$ \; 
+      			\tcp{Query batch of variants from $\Phi$.}    			
+    			$\mathcal{B}_{G} \gets VarGen(\Phi, \sigma_{\mathcal{B}_{N}})$ \; 
     			% perform a sampling op. from the probability density described by the GMM we traverse the network layers in a backwards direction, returns a batch of samples based on the prototype responses from the forward call on xs
-    			\tcp{Add generated samples to $\mathcal{D}_{G}$.}
-    			$\mathcal{D}_{G} \gets UpdateData(\mathcal{B}_{G})$
+    			\tcp{Add gen. samples to $\mathcal{X}_{G}^t$.}
+    			$\mathcal{X}_G^t \gets UpdateData(\mathcal{B}_{G})$
     		}
-    		\For{$\mathcal{B}_{M} \sim (\mathcal{D}_{R_t} \cup \mathcal{D}_{G_t})$}{
-    			\tcp{Update selected prototype of $\Phi$.}
+    		\For{$\mathcal{B}_{M} \sim (\mathcal{X}^{t} \cup \mathcal{X}_{G}^t)$}{
+    			\tcp{Update $\Phi$ and $\Theta$}
     			% Update GMM
-    			$\Phi \gets SGD(\mathcal{B}_{M})$\;
-    			\tcp{Update AR solver.}
+    			$\Phi \gets SGD(\mathcal{B}_{M})$\; $\Theta \gets SGD(\Phi(\mathcal B_M), Y_t)$\;
+    			%\tcp{Update AR solver.}
     			% Classifier with merged batch
-    			$\Theta \gets SGD(\Phi(\mathcal B_M), Y_t)$\;
+    			%$\Theta \gets SGD(\Phi(\mathcal B_M), Y_t)$\;
     		}
     	}
     	%TODO \caption{do we need a caption here?}